2022
DOI: 10.3389/feart.2021.790349
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Spatial Equilibrium Evaluation of Regional Water Resources Carrying Capacity Based on Dynamic Weight Method and Dagum Gini Coefficient

Abstract: With the rapid economic development and the acceleration of urbanization, the pressure on the water resources system is becoming intense. As an important indicator of water resources security and sustainable development, the water resources carrying capacity has become a hot issue. To overcome the limitation of commonly used methods for weight determination and to evaluate the regional water resources carrying capacity reasonably, the index weight determined by the Analytic Hierarchy Process method was revised… Show more

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Cited by 18 publications
(10 citation statements)
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References 24 publications
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“…where WFI is the water footprint intensity of each city, and WF r is the WF of each city. The Dagum Gini coefficient decomposition method could be used to analyze intraregional differences, inter-regional differences, and hyper-variance densities in the variables [37,38]. In this study, the Dagum Gini coefficient decomposition method was used to quantify the spatial equilibrium of WFI and reflect the sources of regional differences in WFI.…”
Section: Quantification Of Spatial Equilibrium In Water Footprint Int...mentioning
confidence: 99%
“…where WFI is the water footprint intensity of each city, and WF r is the WF of each city. The Dagum Gini coefficient decomposition method could be used to analyze intraregional differences, inter-regional differences, and hyper-variance densities in the variables [37,38]. In this study, the Dagum Gini coefficient decomposition method was used to quantify the spatial equilibrium of WFI and reflect the sources of regional differences in WFI.…”
Section: Quantification Of Spatial Equilibrium In Water Footprint Int...mentioning
confidence: 99%
“…Equations ( 12) and ( 13) represent the Gini coefficient G jj for region j and the intraregional gap contribution G W , respectively. The formulae for the inter-regional Gini coefficient G jh , the inter-regional net value gap contribution G nb and the hypervariable density contribution G t are given in (14)(15)(16), respectively, where p j = n j/n, s j = n j Ă— Y j/(nĂ— Y , and j = 1, 2 • • • , k. S j refers to the jth region HQAD evaluation level value share [40]. D jh is the effect of relative HQAD levels between regions j and h; see Equation (17).…”
Section: Dagum Gini Coefficientmentioning
confidence: 99%
“…If the value of an evaluation index increases with the evaluation level k, it is referred to as a positive index (PI). Otherwise, it is called a negative index (NI) [64]. Out of 14 evaluation indexes, there are 8 positive indexes (U 11 , U 12 , U 14 , U 31 , U 33 , U 42 , U 43 and U 44 ) and 6 negative indexes (U 13 , U 21 , U 22 , U 23 , U 32 and U 41 ).…”
Section: Calculation Of the Membership Degreementioning
confidence: 99%